Xianbin Gu is an enthusiastic and dedicated instructor. With a passion for computer vision and machine learning, he is committed to advancing knowledge and fostering a stimulating learning environment for students.
Teaching Philosophy
Xianbin Gu's teaching philosophy is rooted in the practical application of knowledge. He believes in equipping his students with not only the theoretical foundations but also the critical thinking skills for excelling in both their academic and professional endeavors.
Research Focus
Xianbin Gu's primary research focus revolves around the computer vision. He is particularly interested in algorithms that can interpret and extract meaning from visual information. This area of study presents endless possibilities for innovation and problem-solving. He is committed to pushing the boundaries of knowledge in this area and seeking inspiration in collaborative opportunities with fellow academics and experts.
Education
PhD, Information Science
University of Otago
Select Publications
- Gu, Xianbin, and Martin Purvis. "Image segmentation with superpixel based covariance descriptor." Pacific-Asia Conference on Knowledge Discovery and Data Mining. Springer, Cham, 2016
- Gu, Xianbin, Jeremiah D. Deng, and Martin K. Purvis. "Improving superpixel-based image segmentation by incorporating color covariance matrix manifolds." 2014 IEEE International Conference on Image Processing (ICIP). IEEE, 2014
- • Gu, Xianbin, and Xuying LI. "Empirical analysis on long memory property of Baltic dry index." Journal of Shanghai Maritime University 30.1 (2009): 40-44
- Introduction to Computer Science
- Information Visualization